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Conflict-free optimal motion planning for parallel aerial 3D printing using multiple UAVs
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0009-0004-8990-2066
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-3557-6782
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-0126-1897
2024 (English)In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 246, article id 123201Article in journal (Refereed) Published
Abstract [en]

This article introduces a novel collaborative optimal motion planning framework for parallel aerial 3D printing. The proposed novel framework is efficiently capable of handling conflicts between the utilized Unmanned Aerial Vehicles (UAVs), as they follow predefined paths, allowing for a seamless enhancement of aerial 3D printing capabilities by employing multiple UAVs to collaborate in a parallel printing process. The established approach ingeniously formulates UAVs’ motion planning as a multi-constraint optimization problem, ensuring minimal adjustments to their velocities within specified limits. This guarantees smooth and uninterrupted printing while preventing collisions and adhering to the requirements of aerial printing. To substantiate the effectiveness of our proposed motion planning algorithm, an extensive array of simulation studies have been undertaken, encompassing scenarios where multiple UAVs engage in the fabrication of diverse construction shapes. The overall novel concept is being extensively validated in simulations, while the obtained results promise for enhancing the viability and advancing the landscape of aerial additive manufacturing.

Place, publisher, year, edition, pages
2024. Vol. 246, article id 123201
Keywords [en]
Aerial 3D printing, Parallel printing, Conflict resolution, Multi-agent, Robotics
National Category
Robotics
Research subject
Robotics and Artificial Intelligence
Identifiers
URN: urn:nbn:se:ltu:diva-103866DOI: 10.1016/j.eswa.2024.123201ISI: 001164176400001Scopus ID: 2-s2.0-85182503125OAI: oai:DiVA.org:ltu-103866DiVA, id: diva2:1830498
Note

Validerad;2024;Nivå 2;2024-01-22 (signyg);

Full text license: CC BY-4.0

Available from: 2024-01-23 Created: 2024-01-23 Last updated: 2024-04-04Bibliographically approved

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Stamatopoulos, Marios-NektariosBanerjee, AvijitNikolakopoulos, George

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